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All Journal Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Jurnal Indonesia : Manajemen Informatika dan Komunikasi
Rouf, Erik Halma
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Computer Science & IT Languange, Linguistic, Communication & Media Library & Information Science

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Evaluasi Keamanan Sistem Informasi Rumah Sakit: Metode Pengujian ISO 27001 di RS Khusus Mata Purwokerto Akmal, Rafii Nur; Tarwoto; Deni Dwi Susilo; Rouf, Erik Halma; Kodir
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 6 No. 1 (2025): Januari
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jimik.v6i1.1172

Abstract

As service quality becomes paramount, ICT governance is increasingly important for organizations. This study will audit Purwokerto Eye Specialty Hospital's SIMRS against ISO/IEC 27001 standards to evaluate its information security posture. The implemented Hospital Management Information System (SIMRS) aims to support the integration of services and administrative processes, but faces various security challenges such as data loss and potential manipulation. The audit was conducted through observation, interviews, and analysis of existing security policies. The audit results show that information security incident management is in accordance with procedures, including handling, reporting, and corrective actions, with a fairly high level of security maturity. The study recommends periodic evaluation and security enhancements to ensure system resilience against future threats.
Determining The Loan Feasiblity of Bank Customers Using Naïve Bayes, K-Nearest Neighbors And Linear Regression Algorithms Pratiwi, Aniec Anafisah; Saraswati, Wahyuning Tyas; Ardiansyah, Rizky Firman; Rouf, Erik Halma; Pratama, Adhi
Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Vol. 6 No. 3 (2023): Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI)
Publisher : Utility Project Solution

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Abstract

In the financial industry, lending to customers is one of the core activities in the financial sector which has a significant impact on the economy and business growth. Credit is the provision of money or bills that can be equated with it, based on a loan agreement between banks and other parties that requires the agreement to repay the debt after a certain period of time by providing interest. However, the process within these financial institutions needs to assess the feasibility of granting credit to customers who apply for credit. To facilitate the determination of eligibility for granting credit to customers, an accurate and effective analytical method is needed to help solve problems in determining the eligibility classification for granting credit to customers by applying the Naive Bayes, K-Nearest Neighbors (K-NN) and Linear Regression algorithms. Based on the results of the tests that have been carried out using the three algorithms obtained, the results show an accuracy value on K-NN of 87.837%, calculations using the Naïve Bayes algorithm have an accuracy value of 88.917%, while calculations using the Linear Regression algorithm produce a Mean absolute error value of 6.703. It can be concluded that in bank creditworthiness fraud using the Naïve Bayes algorithm method is more accurate when compared to the K-NN and Linear Regression algorithms
Co-Authors Akmal, Rafii Nur Ardiansyah, Rizky Firman Deni Dwi Susilo Kodir Pratama, Adhi Pratiwi, Aniec Anafisah Saraswati, Wahyuning Tyas Tarwoto